Export
Exports a trained model to an optimized inference format.
Exports are written to a fixed location inside the model directory:
<model_dir>/ |-- exports_onnx/ | `-- <checkpoint_stem>_<onnx_precision>.onnx `-- exports_trt/ `-- <checkpoint_stem>_<onnx_precision>/ `-- trt_metadata.jsonThe export path is not configurable. litpose predict –runtime onnx or –runtime tensorrt reads from these same locations.
TensorRT builds its engine from an existing ONNX export rather than re-tracing the model – run –runtime onnx first for the same –onnx-precision.
usage: litpose export <model_dir> [OPTIONS]
Positional Arguments
- model_dir
path to a model directory
Named Arguments
- --runtime
Possible choices: onnx, tensorrt
inference format to export to. Default: onnx.
Default:
'onnx'- --onnx-precision
Possible choices: fp16, fp32
weight precision baked into the exported file. Unlike litpose predict –precision, this changes the exported weights themselves rather than the precision of a forward pass. For –runtime tensorrt, selects which existing ONNX export to build the engine from. Default: fp16.
Default:
'fp16'- --max-batch-size
only used with –runtime tensorrt. Upper bound of the dynamic-shape batch profile the engine is built for; inference at a batch size above this fails. Default: 8.
Default:
8- --opt-batch-size
only used with –runtime tensorrt. Batch size the engine is optimized for; defaults to –max-batch-size. Correctness holds for any batch size in [1, max-batch-size], but performance is best near this value.